Four analytical methods have been applied to infrared microscopic maps of human skin which contained basal cell carcinoma tumors-namely, point spectroscopy, grayscale functional group mapping, digital staining, and fuzzy C-means (FCM) cluster analysis. Spectroscopic interpretation using point spectroscopy allowed discrimination between normal and tumor-bearing skin components. Functional group mapping provided information on the distribution of lipids, proteins, nucleic acids, and collagen within skin sections. While functional group mapping only allowed examination of one material (or a ratio of two materials) at a time, a new approach termed digital staining allowed visualization of the distribution of up to three materials at one time. Digital staining thus gave a more detailed understanding of the tissue section. Finally, application of FCM cluster analysis, a nonsubjective, unsupervised classification methodology, allowed us to group spectra into five distinct clusters, which correlated to distinct tissue components in skin. Tumor-bearing skin was clearly separated from normal skin. When different analytical methods are used in conjunction, a unique understanding of tissues can be obtained. Our results demonstrate that infrared microscopy has potential for the pathological diagnosis of skin tumors.